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shomechakraborty

Scientific Tools MCP Server

literature_search

Search scientific literature across PubMed, arXiv, and Semantic Scholar to retrieve structured results with abstracts, authors, and citation counts. Filter by date range and research field.

Instructions

Search scientific literature across PubMed, arXiv, and Semantic Scholar. Returns structured results with titles, abstracts, authors, publication years, and citation counts. Supports date range filtering and field-specific queries.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSearch query — natural language or Boolean operators supported
max_resultsNoMaximum results per source (1–20, default 5)
sourcesNoSources to search (default: all three)
year_fromNoFilter results from this year onwards
year_toNoFilter results up to this year
fieldsNoOptional: filter by research field (e.g. ['biology', 'chemistry'])
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden. It discloses the return structure (titles, abstracts, authors, etc.) and filtering capabilities, but does not mention rate limits, pagination, or behavior under no results. It adds value beyond the tool name but lacks comprehensive disclosure.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences: the first covers the primary function and sources, the second lists return fields and filtering options. No redundant information; every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description mentions return fields. It covers the main use case and filtering, but does not specify pagination or error handling. With 6 parameters, all are explained in schema and description, making it fairly complete for a search tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with good parameter descriptions. The tool description adds additional meaning by stating that the query supports natural language or Boolean operators, that max_results is per source, and that year_from/year_to are filters for date range. It also describes the return fields, providing context beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb (Search), resource (scientific literature), and specifies the sources (PubMed, arXiv, Semantic Scholar). It lists return fields (titles, abstracts, authors, etc.), distinguishing it from sibling tools like analytics or compound_lookup.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for searching scientific literature and mentions supported filters (date range, field-specific queries), but does not explicitly state when to use this tool vs alternatives or when not to use it. No exclusions are given.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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